摘要： 提出了一种基于多重朴素贝叶斯分类算法的检测方法来实现对计算机病毒的近似判别。该法可以克服病毒特征代码扫描法不能识别未知病毒的缺点。在该检测方法的基础上，设计了一个病毒检测网络模型，该模型既可以实现对已知病毒的查杀，又可以对可疑程序行为进行分析评判，最终实现对未知病毒的识别。

关键词: 计算机病毒；多重朴素贝叶斯算法；信息熵；病毒检测

Abstract: A multi-naive Bayes algorithm to detect computer virus approximately is presented in this paper. It can overcome the shortage of normal virus scanner, which could not detect unknown virus. Based on this method, a virus detect network model is also designed. This model is fit for detecting virus in the on-line system; it could detect known and unknown computer virus by analyzing the program’s behavior

Key words: Computer virus; Multi-naive Bayes algorithm; Information entropy; Virus detection